Quantitative Risk & Data Engineer

HITEC; Jersey City (NJ); On-site; USD 68,000 - 127,000; Full time

Benefits offered by this job

Benefits eligible

In-office role (Jersey City)

Job summary

Bank of America is seeking a data-driven professional for Global Risk Analytics in Jersey City, NJ. You will design and implement technical solutions to enhance data, testing, and analytics capabilities for risk management.

Responsibilities include collaborating with stakeholders, building scalable data pipelines, and applying AI governance principles. A strong background in Python, SQL, APIs, and data engineering is expected.

Qualifications

• Bachelor's degree or above in Mathematics, CS, Statistics, Engineering, OR Data Science or equivalent.
• Demonstrated analytical thinking and problem solving.
• Strong communication skills with stakeholders.
• Experience in software engineering and AI development patterns.

Responsibilities

• Apply critical thinking and risk management to design technical solutions for business problems.
• Partner with process/data owners and stakeholders to gather requirements and explain technical concepts.
• Develop scalable analytical solutions using SDLC and AI development patterns.
• Source, validate and analyze data; design scalable data pipelines for large datasets.
• Ensure AI governance, observability, and compliance in deployed solutions.

Skills

Analytical Thinking

Communication & Stakeholder Management

Software Engineering & AI Development

Data Engineering & Analytics

Oral Communications

Written Communications

Attention to Detail

Change Management

Collaboration

Presentation Skills

Education

Bachelor's degree or above in relevant fields

Tools

Python

APIs

SQL

Databases

Job description

Bank of America is seeking a data-driven professional for Global Risk Analytics in Jersey City, NJ. You will design and implement technical solutions to enhance data, testing, and analytics capabilities for risk management.

Responsibilities include collaborating with stakeholders, building scalable data pipelines, and applying AI governance principles. A strong background in Python, SQL, APIs, and data engineering is expected.